This paper is based on the Lanchester Lecture of the Royal Aeronautical Society held in London, UK, in October 2023. The lecture discussed the advances in computational modeling of separated flows in aerospace applications since Elsenaar’s Lanchester Lecture in 2000. Elsenaar’s efforts focused on assumptions primarily associated with separation for steady inflow and a static (non-moving) vehicle or component. Since that time, significant advancements in computational hardware, coupled with substantial investments in the development of algorithms and solvers, have led to important breakthroughs in the field. In particular, computational aerodynamics techniques are currently applied to complex aerospace problems that include unsteady or dynamic considerations, such as dynamic stall and gusts, which are discussed. A perspective of the technology developed over the past quarter-century, highlighting their importance to computational aerodynamics is discussed. Finally, the potential of future areas of development, such as machine learning, that may be exploited for the next generation of computational aerodynamics applications is explored.

This paper investigates a method for estimating emissions from hybrid-electric aircraft, providing a qualitative assessment of their potential environmental benefits. Limited data availability poses challenges, discussed in this study, for its rigorous evaluation. Proper characterisation of both ${{C}}{{{O}}_{{2}}}$ and non-${{C}}{{{O}}_{{2}}}$ emissions across the operating envelope is crucial. Existing databases and predictive models for turboshaft engines for full-thermal regional aircraft may not be reliable for hybrid-electric configurations, which could operate under uncommon conditions, as low thermal power supply during specific flight phases. This uncertainty highlights the limitations of current emission prediction models. The first of the present study examines non-${{C}}{{{O}}_{{2}}}$ emissions (${{N}}{{{O}}_{{x}}}$, HC, ${{S}}{{{O}}_{{2}}}$, CO) from hybrid-electric aircraft optimised for minimum block fuel, comparing them with those from thermal competitors. The second part evaluates ${{C}}{{{O}}_{{2}}}$ emissions, considering both in-flight and electricity generation contributions. Results indicate that hybrid-electric configurations could reduce non-${{C}}{{{O}}_{{2}}}$ emissions for both the entire mission and the landing-take-off cycle. However, ${{C}}{{{O}}_{{2}}}$ reductions are only significant for short design ranges and could be marginal if electricity generation does not shift to fully renewable sources.

Under the coupling effect of node position deviation, joint clearance and wear factors, the complex landing gear retraction mechanism suffers from low kinematic accuracy, slow retraction performance and shortened reliable life. Addressing these issues, a time-dependent reliability analysis and optimisation design method for the kinematic accuracy of the retraction mechanism is proposed, considering the uncertainty of node position deviation, initial clearance, and dynamic multi-joint wear. Initially, a wear prediction model and a dynamic model of the retraction mechanism considering node position deviation and joint clearance are established to analyse their influence on retraction accuracy and joint wear depth. Subsequent retraction testing under various working conditions is conducted to ascertain the critical failure condition and validate the simulation model. The time-dependent kinematic accuracy reliability model, accounting for the dynamic evolution of wear clearance, is then established to assess reliability variation with retraction cycles. Finally, the reliability optimisation design focusing on hole-axis matching accuracy aims to strike a balance between accuracy cost and reliability, thereby enhancing performance and prolonging operational life.

Aerodynamic investigations are crucial for the efficient design of Lighter-than-Air (LTA) systems. This study explores the aerodynamic characteristics of conventional and multi-lobed airships, motivated by the growing interest in LTA systems due to advancements in materials science, energy sources, aerodynamics, propulsion technology and control systems. The study employs the k-epsilon turbulence model, which is well-suited for turbulent flow simulations, and the Semi-Implicit Method for Pressure Linked Equations (SIMPLE) algorithm, known for its effectiveness in pressure-velocity coupling in fluid dynamics simulations. The results indicate that multi-lobed airships offer enhanced aerodynamic efficiency over conventional designs. Detailed analyses of lift and drag coefficients provide insights into aerodynamic performance, guiding the optimisation of airship designs for improved efficiency. The findings of this study support the development of more aerodynamically efficient airship designs, which can serve as cost-effective, energy-efficient and quieter alternatives to traditional aircraft, particularly for applications such as surveillance, cargo transport and scientific research.

The dynamic model of the distributed propulsion vehicle faces significant challenges due to several factors. The primary difficulties arise from the strong coupling between multiple power units and aerodynamic rudder surfaces, the interaction between thrust and vehicle dynamics, and the complexity of the aerodynamic model, which includes high-dimensional and high-order variables. To address these challenges, wind tunnel tests are conducted to analyse the aerodynamic characteristics and identify variables affecting the aerodynamic coefficients. Subsequently, a deep neural network is employed to investigate the influence of the power system and aerodynamic rudder on the aerodynamic coefficients. Based on these findings, a multi-dynamic coupled aerodynamic model is developed. Furthermore, a control-oriented nonlinear dynamics model for the distributed propulsion vehicle is established, and a flight controller is designed. Finally, closed-loop simulations for the climb, descent and turn phases are performed, validating the effectiveness of the established model.

This paper presents the development and implementation of a comprehensive system for acquiring telemetry from Alsat-2A and Alsat-2B satellites, whose orbits are phased 180 degrees apart, utilising the CDM600 demodulator. Integral to this system is an automatic learning module leveraging machine learning algorithms to optimise circular polarisation selection based on reception conditions. The software segment manages the demodulator, user interface, and coordinates the machine learning algorithm, drawing insights from historical polarisation data to construct predictive models for optimal polarisation selection. Through the integration of machine learning, this system aims to enhance telemetry signal reception quality, contributing to the success (Alsat-2A was launched on 12 July 2010, and Alsat-2B on 26 September 2016) of satellite missions.

In response to the requirements for assessing the impact safety of aero-engines, a high-fidelity numerical simulation method based on overset mesh technology for six-degree-of-freedom rigid body motion is proposed. A gas-solid two-phase flow model is established, coupling two types of ice-debris (externally ingested ice and internally delaminated ice) with air, to analyse their behaviour in a dorsal S-shaped inlet with a diffusion ratio of 1.3. Results indicate that the ice-debris entering from the upper region of the entrance section exerts the most significant distortion on the total-pressure at the engine inlet. Additionally, the behaviour of ice-debris is determined by its angle with respect to the incoming flow direction and the shape of ice. Furthermore, although the ice-debris detached from the entrance section poses no immediate threat to the engine, the prolonged acceleration by high-speed airflow, with velocity increments exceeding 45 m/s, results in a higher kinetic energy carried upon impact with the inlet walls. Regarding externally ingested ice-debris, a smaller initial velocity corresponds to a higher probability of impacting the engine, accompanied by a significant increase in velocity. For instance, the irregular ice-debris ingested at an initial velocity of 6 m/s can experience velocity amplification exceeding 590%.

This publication presents the results of a numerical analysis aimed at assessing the applicability of thermal tip clearance control (TCC) to the fore-to-last stage of a 10-stage high-pressure compressor system. The chosen geometry is representative for the HPC rear stages of a modern middle-sized turbofan, designed for large business jets and regional airliners. Simplified models for two TCC concepts were implemented, isolated and in combination: external impingement cooling and heat pipes. The analysis was performed by means of finite-element thermostructural simulations. Transient operational cycles, derived from a meanline model, along with empiric correlations for heat convection provided the required boundary conditions. Qualitative similarity to selected previous works in terms of temperature, stress and clearance evolutions was achieved. The combination of concepts demonstrated its potential as a TCC system with up to 0.45% reductions in rotor and stator clearances. Calculated heat pipe temperatures and heat fluxes were inside the estimated operational limitations. Regarding stresses, some local concentrations were observed, without significant impact in critical stress regions. A slam cycle analysis showed that, while blade rubbing remains a possibility, it can be mitigated by robust cooling control. All in all, the concept was deemed worthy of more detailed studies.

This study investigates the dynamics of water droplets within a Batchelor vortex. Such an analytically described flow structure serves here as a model that may capture the essence of a trailing vortex. A Lagrangian approach is used to analyse the coupling between droplet motion and the flow field generated by the vortex. Under certain thermodynamic and hydrodynamic conditions, droplets may undergo evaporation and condensation when circulating the vortex core due to sharp changes in the environmental conditions induced by the vortex. The vortex-induced pressure drop is quantified using a non-dimensional vortex Euler number, revealing conditions required for condensation initiation within the vortex core. The onset of condensation is characterised by defining a mass transfer coefficient, indicating the direction and extent of mass transfer to the droplets. Our study uncovered a distinct clustering phenomenon linked to the initial Stokes number, with droplets showing a tendency to aggregate at higher Stokes numbers. The presented model may offer valuable insights into droplet dynamics within trailing vortices, contributing to improved modelling and prediction of droplet transport phenomena near trailing vortices.

The impinging–freezing of supercooled water droplets (SLDs) is the root cause of aircraft icing. This work presented an experimental investigation of a millimeter-sized supercooled droplet (−10 $^\circ {\rm{C}}$) impact onto cold surfaces. For the majority of the current research on freezing behaviour, the quantitative analysis of impingement contributions was neglected. The present study established prediction models for the frozen area ratio, initial freezing height and solidification time by changing Weber number and Stefan number. The results showed that with the decrease in surface temperatures, the maximum spreading factor and the peak height factor were unchanged; however, the receding velocity of the liquid film reduced. Besides, regardless of the three freezing modes (quasi-static, instantaneous and delayed), the frozen area ratio consistently increased with decreasing Weber number. For the Stefan number exceeded 0.12, the frozen area ratio increased with decreasing surface temperature; otherwise, it was independent of the surface temperature. In addition, the initial height of asymmetrical frozen droplets was characterised using the ‘two-ellipse’ method, revealing an inverse proportionality to the square root of the frozen area ratio. Furthermore, the solidification time of the hemisphere and pancake frozen droplets shortened with the decrease in the initial height and surface temperature. This fundamental study provides valuable insights for understanding aircraft icing and optimising anti-icing systems.

The cavities over the re-entry vehicle alter the aerothermodynamic properties, leading to enhanced thermal protection as well as effective aerothermodynamic performance. This paper investigates the estimation of aerothermodynamic properties over a re-entry vehicle with different types of cavities on the frontal face of the vehicle. The direct simulation Monte Carlo (DSMC) simulation of hypersonic flow over the Crew module Atmospheric Re-entry Experiment (CARE) capsule was simulated with the re-entry velocity of 7,422 m/s and the freestream temperature of 225 K at an altitude of 110 km. A transient flow Knudsen number of 0.1 and air consists of 78.09% of ${N_2}$ and 21.91% of ${O_2}$ are used in the simulations. Two types of cavities, namely trapezoidal and the semi-circular cavity on the frontal face of the re-entry vehicle with different length to depth ratios, are analysed. The simulation results show that the recirculation regions are formed at the base of the cavity in the case of a cavity with sharp corners, whereas in the case of a cavity with rounded corners, the recirculation formed at the lip of the cavity for both trapezoidal and the semi-circular cavities. Increasing the length and depth of the cavity leads to smaller decrement in the drag when compared to the capsule without cavity for both trapezoidal and the semi-circular cavities. The heat flux is low for a cavity with the small L/D ratio (L/D = 0.5) for both fixed length and depth for trapezoidal-type cavity, whereas for large L/D ratio (L/D = 1.5) increasing the length of the cavity increases the overall heat flux.

This paper presents an improved signal-processing method based on the Hilbert-Huang transform (HHT), which is applied to the fault feature extraction of the aerospace generator rotating rectifier (AGRR). Initially, the excitation current of the alternating-current (AC) exciter is utilised as measurable information for data collection. Subsequently, the HHT is processed with variational mode decomposition (VMD), followed by the improvement of the variational Hilbert-Huang transform (VHHT) using particle swarm optimisation (PSO) to determine the modal decomposition number and the secondary penalty factor. Finally, the proposed PSO-VHHT method is compared with several other signal processing-based feature extraction methods through both simulated and practical experiment data, and an analysis of the diagnostic performance of these methods is also conducted.

The unpredictable benefits and low operational costs of unmanned aerial vehicles (UAVs) compared to their conventional counterparts caused a tremendous change in commercial and military concepts, and different solutions to problems regarding modern aerial vehicles were tried to further improve flight and job performances. One of the most challenging problems about the UAVs is known as the path planning problem, and a solution should satisfy some objectives related to the enemy anti-air weapons, fuel or battery consumption, and manoeuvre capability of the UAV being operated optimally. Immune plasma algorithm (IP algorithm or IPA) is a recent meta-heuristic optimiser, and its competitive performance has been validated over a set of engineering problems. In this study, a greedy initialiser that is responsible for generating a population of IPA was first introduced. Also, the treatment schema of the IPA was completely redesigned for more robust and detailed search characteristics without requiring either IPA-specific control parameters or their subtle configurations. The new IPA-based path planner, called greedy initialiser IPA (gintIPA), was tested by using three battlefields and 12 test cases belonging to them, and the obtained results were compared with the results of the well-known meta-heuristic techniques. Comparative studies showed that gintIPA is capable of planning more robust and safe UAV paths than other techniques for $91.6$ of all test cases. The proposed greedy initialiser gives a chance to start optimisation with qualified individuals and the newly designed treatment schema improving both exploitation and exploration routines significantly contributes to the gintIPA when outperforming other path planners.

To capture the airspeed-dependent dynamics of flexible aircraft, high-order aeroservoelastic systems can generally be expressed as linear parameter-varying (LPV) models. This paper presents a comprehensive model order reduction and control design process for grid-based LPV systems, and takes the flexible aircraft FLEXOP as an example for verification. The LPV model order reduction method is extended from projection-based linear time-invariant methods through construction of continuous transformations. The corresponding algorithm can be programmed to automatically perform the model order reduction for LPV systems and simultaneously ensure the state consistency between grid points and the continuity of state-space data interpolation. By applying this method, a 680th-order high-fidelity LPV model of the FLEXOP aircraft is reduced to a control-oriented model with only 19 states. Considering that the frequencies of rigid-body and flexible modes are close under certain parameter conditions, an integrated design approach for rigid-flexible coupling control is employed in this paper. Instead of separately designing a baseline rigid-body flight controller and a flutter suppression controller for each unstable flexible mode, a parameter-dependent dynamic output-feedback controller is designed. The resulting controller effectively expands the flutter-free flight envelope, ensuring rigid-body attitude and velocity tracking performance while stabilising the two originally unstable flutter modes.